Summary of 2_DecisionTree
<< Go back
Decision Tree
- n_jobs: -1
- criterion: gini
- max_depth: 3
- explain_level: 2
Validation
- validation_type: split
- train_ratio: 0.75
- shuffle: True
- stratify: True
Optimized metric
logloss
Training time
7.3 seconds
Metric details
|
score |
threshold |
| logloss |
1.05791 |
nan |
| auc |
0.54129 |
nan |
| f1 |
0.554622 |
0 |
| accuracy |
0.593023 |
0.813025 |
| precision |
0.473684 |
0.709416 |
| recall |
0.970588 |
0 |
| mcc |
0.123319 |
0.170543 |
Confusion matrix (at threshold=0.813025)
|
Predicted as 0 |
Predicted as 1 |
| Labeled as 0 |
44 |
8 |
| Labeled as 1 |
27 |
7 |
Learning curves
Decision Tree
Tree #1
Rules
if (feature_354 > -0.88) and (feature_383 > -0.399) and (feature_214 > -1.377) then class: 0 (proba: 82.95%) | based on 129 samples
if (feature_354 > -0.88) and (feature_383 <= -0.399) and (feature_480 > -0.296) then class: 1 (proba: 70.45%) | based on 44 samples
if (feature_354 <= -0.88) and (feature_377 > -1.05) and (feature_247 <= 0.459) then class: 1 (proba: 91.18%) | based on 34 samples
if (feature_354 > -0.88) and (feature_383 <= -0.399) and (feature_480 <= -0.296) then class: 0 (proba: 76.67%) | based on 30 samples
if (feature_354 > -0.88) and (feature_383 > -0.399) and (feature_214 <= -1.377) then class: 1 (proba: 71.43%) | based on 14 samples
if (feature_354 <= -0.88) and (feature_377 <= -1.05) then class: 0 (proba: 100.0%) | based on 4 samples
if (feature_354 <= -0.88) and (feature_377 > -1.05) and (feature_247 > 0.459) then class: 0 (proba: 100.0%) | based on 3 samples
Permutation-based Importance
Confusion Matrix
Normalized Confusion Matrix
ROC Curve
Kolmogorov-Smirnov Statistic
Precision-Recall Curve
Calibration Curve
Cumulative Gains Curve
Lift Curve
<< Go back
Automatic Exploratory Data Analysis Report
